Report last updated Mon May 23 19:08:37 2016.
In this section we will see descriptive figures about quality of the data, reads with adapter, reads mapped to miRNAs, reads mapped to other small RNAs.
After adapter removal, we can plot the size distribution of the small RNAs.
Number of miRNAs with > 3 counts.
| colSums(counts > 10) | |
|---|---|
| A201_Day0 | 348 |
| A200_Day0 | 380 |
| A196_Day0 | 363 |
| A190_Day28 | 389 |
| A189_Day14 | 374 |
| A181_Day7 | 380 |
| A180_Day7 | 420 |
| A178_Day3 | 399 |
| A172_Day2 | 387 |
| A167_Day1 | 338 |
| A165_Day1 | 369 |
| A89_Day28 | 365 |
| A86_Day28 | 376 |
| A85_Day14 | 355 |
| A84_Day14 | 394 |
| A80_Day7 | 392 |
| A75_Day3 | 373 |
| A74_Day3 | 409 |
| A70_Day2 | 430 |
| A69_Day2 | 423 |
| A63_Day1 | 372 |
Number of miRNAs with > 3 counts.
| colSums(counts > 10) | |
|---|---|
| A201_Day0 | 75 |
| A200_Day0 | 93 |
| A196_Day0 | 82 |
| A190_Day28 | 87 |
| A189_Day14 | 80 |
| A181_Day7 | 88 |
| A180_Day7 | 103 |
| A178_Day3 | 91 |
| A172_Day2 | 90 |
| A167_Day1 | 71 |
| A165_Day1 | 86 |
| A89_Day28 | 76 |
| A86_Day28 | 85 |
| A85_Day14 | 73 |
| A84_Day14 | 86 |
| A80_Day7 | 79 |
| A75_Day3 | 78 |
| A74_Day3 | 94 |
| A70_Day2 | 107 |
| A69_Day2 | 102 |
| A63_Day1 | 87 |
The data was analyzed with seqcluster
This tools used all reads, uniquely mapped and multi-mapped reads. The first step is to cluster sequences in all locations they overlap. The second step is to create meta-clusters: is the unit that merge all clusters that share the same sequences. This way the output are meta-clusters, common sequences that could come from different region of the genome.
In this table 1 means % of the genome with at least 1 read, and 0 means % of the genome without reads.
The normal value for human data with strong small RNA signal is: 0.0002. This will change for smaller genomes.
Number of reads in the data after each step:
Check complex meta-clusters: This kind of events happen when there are small RNA over the whole genome, and all repetitive small rnas map to thousands of places and sharing many sequences in many positions. If any meta-cluster is > 40% of the total data, maybe it is worth to add some filters like: minimum number of counts -e or --min--shared in seqcluster prepare
A201_Day0 A200_Day0 A196_Day0 A190_Day28 A189_Day14 A181_Day7
A180_Day7 A178_Day3 A172_Day2 A167_Day1 A165_Day1 A89_Day28 A86_Day28
A85_Day14 A84_Day14 A80_Day7 A75_Day3 A74_Day3 A70_Day2 A69_Day2
A63_Day1
Number of miRNAs with > 10 counts.
| colSums(clus_ma > 10) | |
|---|---|
| A201_Day0 | 536 |
| A200_Day0 | 545 |
| A196_Day0 | 559 |
| A190_Day28 | 556 |
| A189_Day14 | 555 |
| A181_Day7 | 554 |
| A180_Day7 | 564 |
| A178_Day3 | 574 |
| A172_Day2 | 546 |
| A167_Day1 | 547 |
| A165_Day1 | 577 |
| A89_Day28 | 536 |
| A86_Day28 | 561 |
| A85_Day14 | 578 |
| A84_Day14 | 563 |
| A80_Day7 | 553 |
| A75_Day3 | 564 |
| A74_Day3 | 550 |
| A70_Day2 | 562 |
| A69_Day2 | 563 |
| A63_Day1 | 559 |
DESeq2 is used for this analysis.
## Comparison: fa_model_mirna {.tabset}
out of 645 with nonzero total read count
adjusted p-value < 0.1
LFC > 0 (up) : 163, 25%
LFC < 0 (down) : 133, 21%
outliers [1] : 1, 0.16%
low counts [2] : 88, 14%
(mean count < 1)
[1] see ‘cooksCutoff’ argument of ?results
[2] see ‘independentFiltering’ argument of ?results
NULL
Differential expression file at: fa_model_mirna.tsv
Normalized counts matrix file at: fa_model_mirna_log2_counts.tsv
Plot top 9 genes
| baseMean | log2FoldChange | lfcSE | stat | pvalue | padj | symbol | description | Day14vsDay0 | Day1vsDay0 | Day2vsDay0 | Day3vsDay0 | Day7vsDay0 | absMaxLog2FC | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| mmu-miR-21a-3p | 3349.90195 | 0.2092341 | 0.2123191 | 373.2788 | 0 | 0 | mmu-miR-21a-3p | mmu-miR-21a-3p | 1.2023999 | 2.6461098 | 3.1643137 | 2.7118794 | 2.2483118 | 3.1643137 |
| mmu-miR-21a-5p | 235757.69370 | 0.5885233 | 0.1674390 | 323.3068 | 0 | 0 | mmu-miR-21a-5p | mmu-miR-21a-5p | 1.5993843 | 2.0354839 | 2.4120192 | 2.3303773 | 2.3425021 | 2.4120192 |
| mmu-miR-92a-1-5p | 139.77162 | -0.1588406 | 0.1761096 | 293.8874 | 0 | 0 | mmu-miR-92a-1-5p | mmu-miR-92a-1-5p | 0.3916372 | 1.5100673 | 1.6814937 | 1.2625307 | 0.8592778 | 1.6814937 |
| mmu-miR-181c-5p | 5177.32928 | 0.7730872 | 0.1141849 | 270.6441 | 0 | 0 | mmu-miR-181c-5p | mmu-miR-181c-5p | 0.6225336 | -0.4106138 | -0.4550042 | -0.5910839 | 0.1610376 | 0.6225336 |
| mmu-miR-375-3p | 1831.43198 | 0.6415690 | 0.1500521 | 249.5976 | 0 | 0 | mmu-miR-375-3p | mmu-miR-375-3p | 1.5341903 | 0.2266603 | 1.1013174 | 1.5199590 | 1.7979345 | 1.7979345 |
| mmu-miR-130b-3p | 121.24753 | 0.9038785 | 0.2313726 | 235.2099 | 0 | 0 | mmu-miR-130b-3p | mmu-miR-130b-3p | 1.8024114 | 0.7083430 | 1.6076363 | 2.4460588 | 2.4122506 | 2.4460588 |
| mmu-miR-199a-5p | 1494.91668 | 1.1819872 | 0.1614447 | 225.4967 | 0 | 0 | mmu-miR-199a-5p | mmu-miR-199a-5p | 1.7951627 | 0.2449684 | 0.5223752 | 1.0193132 | 1.7315863 | 1.7951627 |
| mmu-miR-199a-3p | 15543.36157 | 1.1521346 | 0.1641965 | 216.1439 | 0 | 0 | mmu-miR-199a-3p | mmu-miR-199a-3p | 1.6577361 | 0.0145188 | 0.1361008 | 0.6047284 | 1.4022824 | 1.6577361 |
| mmu-miR-199b-3p | 15532.96146 | 1.1525354 | 0.1642081 | 216.0259 | 0 | 0 | mmu-miR-199b-3p | mmu-miR-199b-3p | 1.6577379 | 0.0150815 | 0.1362317 | 0.6042545 | 1.4016804 | 1.6577379 |
| mmu-miR-146b-5p | 1879.08619 | 1.6373420 | 0.2285428 | 211.7384 | 0 | 0 | mmu-miR-146b-5p | mmu-miR-146b-5p | 2.8223531 | 1.1898393 | 1.5489137 | 2.6665250 | 2.7112640 | 2.8223531 |
| mmu-miR-181a-5p | 79471.80435 | 0.4281674 | 0.1028707 | 206.5081 | 0 | 0 | mmu-miR-181a-5p | mmu-miR-181a-5p | 0.2454838 | -0.4277786 | -0.5874128 | -0.6785543 | -0.3003926 | 0.6785543 |
| mmu-miR-15b-5p | 444.43295 | 0.1121891 | 0.1380392 | 204.4162 | 0 | 0 | mmu-miR-15b-5p | mmu-miR-15b-5p | 0.5679018 | 0.4463544 | 0.9437916 | 1.3881331 | 1.2517012 | 1.3881331 |
| mmu-let-7j | 3660.48447 | 0.7473125 | 0.1423042 | 191.9095 | 0 | 0 | mmu-let-7j | mmu-let-7j | 1.4174612 | 0.2660367 | 0.5022776 | 1.0472989 | 1.5061737 | 1.5061737 |
| mmu-miR-18a-5p | 140.48080 | 0.2058626 | 0.2645325 | 189.7141 | 0 | 0 | mmu-miR-18a-5p | mmu-miR-18a-5p | 1.0554008 | 1.6065388 | 2.2486953 | 2.4126605 | 2.0513531 | 2.4126605 |
| mmu-miR-298-5p | 63.44882 | 1.9510187 | 0.4342741 | 189.7205 | 0 | 0 | mmu-miR-298-5p | mmu-miR-298-5p | 3.0350291 | 1.0633386 | 3.1482262 | 4.0225210 | 3.8880722 | 4.0225210 |
| mmu-miR-132-3p | 995.91587 | 1.0972911 | 0.2259190 | 183.9388 | 0 | 0 | mmu-miR-132-3p | mmu-miR-132-3p | 2.3521595 | 2.3004948 | 2.4792479 | 2.5213285 | 2.6462390 | 2.6462390 |
| mmu-let-7i-5p | 28002.55133 | 0.6010586 | 0.1546107 | 178.5984 | 0 | 0 | mmu-let-7i-5p | mmu-let-7i-5p | 1.3966011 | 0.9385165 | 1.4164715 | 1.6881308 | 1.7028061 | 1.7028061 |
| mmu-miR-221-3p | 5762.96983 | -0.0016366 | 0.0879878 | 167.2031 | 0 | 0 | mmu-miR-221-3p | mmu-miR-221-3p | 0.2406472 | 0.8688996 | 0.6301371 | 0.5365345 | 0.3439440 | 0.8688996 |
| mmu-miR-214-3p | 671.15060 | 1.1800627 | 0.2515532 | 163.6752 | 0 | 0 | mmu-miR-214-3p | mmu-miR-214-3p | 2.2324322 | 0.5469246 | 1.6893764 | 2.4875904 | 2.4306447 | 2.4875904 |
| mmu-miR-223-3p | 588.88017 | 1.1182354 | 0.2385065 | 160.3819 | 0 | 0 | mmu-miR-223-3p | mmu-miR-223-3p | 1.7473818 | 1.8978195 | 2.2931158 | 2.5513986 | 2.6457617 | 2.6457617 |
Working with 119 genes
## Comparison: fa_model_novel {.tabset}
out of 255 with nonzero total read count
adjusted p-value < 0.1
LFC > 0 (up) : 35, 14%
LFC < 0 (down) : 21, 8.2%
outliers [1] : 3, 1.2%
low counts [2] : 45, 18%
(mean count < 1)
[1] see ‘cooksCutoff’ argument of ?results
[2] see ‘independentFiltering’ argument of ?results
NULL
Differential expression file at: fa_model_novel.tsv
Normalized counts matrix file at: fa_model_novel_log2_counts.tsv
Plot top 9 genes
| baseMean | log2FoldChange | lfcSE | stat | pvalue | padj | symbol | description | Day14vsDay0 | Day1vsDay0 | Day2vsDay0 | Day3vsDay0 | Day7vsDay0 | absMaxLog2FC | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| mmu-chr2_1617-5p | 15704.04826 | 1.2477818 | 0.1746373 | 209.52844 | 0e+00 | 0.0e+00 | mmu-chr2_1617-5p | mmu-chr2_1617-5p | 1.7027375 | 0.0082195 | 0.0858072 | 0.5345992 | 1.4062735 | 1.7027375 |
| mmu-chr2_1617-3p | 1604.50416 | 1.2688125 | 0.1741413 | 202.95721 | 0e+00 | 0.0e+00 | mmu-chr2_1617-3p | mmu-chr2_1617-3p | 1.8256632 | 0.2348821 | 0.4584559 | 0.9290956 | 1.7115133 | 1.8256632 |
| mmu-chr19_17788-5p | 1870.89106 | 1.7255196 | 0.2440247 | 183.76794 | 0e+00 | 0.0e+00 | mmu-chr19_17788-5p | mmu-chr19_17788-5p | 2.8532472 | 1.1836523 | 1.4959106 | 2.5986829 | 2.7055385 | 2.8532472 |
| mmu-chr10_11097-5p | 28102.83066 | 0.6957317 | 0.1572774 | 158.46900 | 0e+00 | 0.0e+00 | mmu-chr10_11097-5p | mmu-chr10_11097-5p | 1.4408854 | 0.9261011 | 1.3499184 | 1.6070990 | 1.6992468 | 1.6992468 |
| mmu-chr1_555-5p | 667.46643 | 1.2691971 | 0.2622320 | 146.04206 | 0e+00 | 0.0e+00 | mmu-chr1_555-5p | mmu-chr1_555-5p | 2.2758244 | 0.5344898 | 1.6321099 | 2.4187867 | 2.4222843 | 2.4222843 |
| mmu-chr13_13968-5p | 61.65890 | -0.3566850 | 0.2542023 | 138.44277 | 0e+00 | 0.0e+00 | mmu-chr13_13968-5p | mmu-chr13_13968-5p | -0.0269858 | 1.1506837 | 1.5581120 | 0.8687753 | 0.9284907 | 1.5581120 |
| mmu-chr1_555-3p | 115.13914 | 1.3546718 | 0.2391823 | 116.86146 | 0e+00 | 0.0e+00 | mmu-chr1_555-3p | mmu-chr1_555-3p | 1.8908435 | 0.2770808 | 1.0133671 | 1.4400643 | 1.8729387 | 1.8908435 |
| mmu-chr11_11842-5p | 1382.93118 | 0.9296450 | 0.2507180 | 98.17101 | 0e+00 | 0.0e+00 | mmu-chr11_11842-5p | mmu-chr11_11842-5p | 1.0489480 | -0.6201143 | -0.8844405 | -0.0090860 | 0.3996378 | 1.0489480 |
| mmu-chr4_4731-5p | 639.48337 | 1.5006912 | 0.2233972 | 86.16079 | 0e+00 | 0.0e+00 | mmu-chr4_4731-5p | mmu-chr4_4731-5p | 1.7109593 | 1.5824969 | 1.8862033 | 1.8008005 | 1.9147657 | 1.9147657 |
| mmu-chr7_7254-3p | 62.05451 | 0.7366221 | 0.2251416 | 84.25959 | 0e+00 | 0.0e+00 | mmu-chr7_7254-3p | mmu-chr7_7254-3p | 0.7659992 | 0.9640480 | 1.2852468 | 1.6636096 | 1.0832762 | 1.6636096 |
| mmu-chr11_11562-5p | 7094.45722 | 0.2026164 | 0.0778748 | 83.73320 | 0e+00 | 0.0e+00 | mmu-chr11_11562-5p | mmu-chr11_11562-5p | 0.2720386 | -0.1950919 | -0.2988935 | -0.1130372 | -0.0034623 | 0.2988935 |
| mmu-chrX_18627-3p | 777.30582 | -0.0683547 | 0.1333196 | 71.97971 | 0e+00 | 0.0e+00 | mmu-chrX_18627-3p | mmu-chrX_18627-3p | -0.4616503 | -0.6040915 | -0.6853519 | -0.8646916 | -0.6407676 | 0.8646916 |
| mmu-chr4_4731-3p | 11.64074 | 5.5864065 | 1.2446180 | 71.53433 | 0e+00 | 0.0e+00 | mmu-chr4_4731-3p | mmu-chr4_4731-3p | 5.9332551 | 5.8722774 | 6.1835144 | 5.3788624 | 6.9622301 | 6.9622301 |
| mmu-chr14_14324-5p | 650.20373 | 0.1321476 | 0.1342842 | 69.72374 | 0e+00 | 0.0e+00 | mmu-chr14_14324-5p | mmu-chr14_14324-5p | 0.2733892 | 0.8354807 | 0.6416453 | 0.5808258 | 0.7394271 | 0.8354807 |
| mmu-chr12_13064-5p | 242.72311 | -0.2393021 | 0.2138295 | 61.63439 | 0e+00 | 0.0e+00 | mmu-chr12_13064-5p | mmu-chr12_13064-5p | -0.7873948 | -0.1124744 | -0.6147547 | -0.8729946 | -1.4391207 | 1.4391207 |
| mmu-chr7_7254-5p | 352.21891 | 0.1637386 | 0.1375269 | 59.25820 | 0e+00 | 0.0e+00 | mmu-chr7_7254-5p | mmu-chr7_7254-5p | 0.3285514 | 0.1666189 | 0.5267945 | 0.7043941 | 0.7707181 | 0.7707181 |
| mmu-chr8_8358-5p | 11893.87663 | -0.6576385 | 0.5002037 | 55.69714 | 0e+00 | 0.0e+00 | mmu-chr8_8358-5p | mmu-chr8_8358-5p | -0.8809473 | 1.1651061 | 1.5080060 | -1.0549920 | -0.7001651 | 1.5080060 |
| mmu-chr11_11568-3p | 605.58914 | 0.3205571 | 0.1255872 | 46.53153 | 0e+00 | 3.0e-07 | mmu-chr11_11568-3p | mmu-chr11_11568-3p | 0.3391268 | -0.1641964 | -0.1565013 | -0.2148585 | 0.2693321 | 0.3391268 |
| mmu-chr18_17508-5p | 371.97170 | -0.3588681 | 0.1276606 | 42.78688 | 1e-07 | 1.4e-06 | mmu-chr18_17508-5p | mmu-chr18_17508-5p | -0.6669813 | -0.2609442 | -0.4787330 | -0.5794412 | -0.6441856 | 0.6669813 |
| mmu-chr8_9013-5p | 139.09155 | -0.1207145 | 0.2029023 | 40.54146 | 4e-07 | 3.7e-06 | mmu-chr8_9013-5p | mmu-chr8_9013-5p | -1.1053441 | -0.0885767 | -0.1244822 | 0.0506256 | -0.5256979 | 1.1053441 |
Working with 28 genes
## Comparison: fa_model_isomir {.tabset}
out of 9976 with nonzero total read count
adjusted p-value < 0.1
LFC > 0 (up) : 1140, 11%
LFC < 0 (down) : 906, 9.1%
outliers [1] : 1, 0.01%
low counts [2] : 3095, 31%
(mean count < 1)
[1] see ‘cooksCutoff’ argument of ?results
[2] see ‘independentFiltering’ argument of ?results
NULL
Differential expression file at: fa_model_isomir.tsv
Normalized counts matrix file at: fa_model_isomir_log2_counts.tsv
Plot top 9 genes
| baseMean | log2FoldChange | lfcSE | stat | pvalue | padj | symbol | description | Day14vsDay0 | Day1vsDay0 | Day2vsDay0 | Day3vsDay0 | Day7vsDay0 | absMaxLog2FC | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| mmu-miR-21a-5p.iso.t5:0.t3:C.ad:C.mm:0 | 11278.35779 | 0.2023678 | 0.2104789 | 544.8132 | 0 | 0 | mmu-miR-21a-5p.iso.t5:0.t3:C.ad:C.mm:0 | mmu-miR-21a-5p.iso.t5:0.t3:C.ad:C.mm:0 | 1.1912110 | 3.5583135 | 3.6269413 | 3.1720696 | 2.5279801 | 3.6269413 |
| mmu-miR-21a-5p.iso.t5:A.t3:0.ad:0.mm:0 | 846.80622 | 0.1694778 | 0.1776450 | 531.5104 | 0 | 0 | mmu-miR-21a-5p.iso.t5:A.t3:0.ad:0.mm:0 | mmu-miR-21a-5p.iso.t5:A.t3:0.ad:0.mm:0 | 1.3519726 | 2.1691581 | 2.8615896 | 2.8224250 | 2.4868270 | 2.8615896 |
| mmu-miR-21a-5p.iso.t5:0.t3:C.ad:A.mm:0 | 5274.01122 | -0.0478811 | 0.1617310 | 515.1055 | 0 | 0 | mmu-miR-21a-5p.iso.t5:0.t3:C.ad:A.mm:0 | mmu-miR-21a-5p.iso.t5:0.t3:C.ad:A.mm:0 | 0.9437825 | 1.9337577 | 2.6396474 | 2.4719199 | 2.0068352 | 2.6396474 |
| mmu-miR-21a-5p.iso.t5:A.t3:C.ad:0.mm:0 | 58.20176 | -0.3647279 | 0.4794563 | 467.9483 | 0 | 0 | mmu-miR-21a-5p.iso.t5:A.t3:C.ad:0.mm:0 | mmu-miR-21a-5p.iso.t5:A.t3:C.ad:0.mm:0 | 1.4586001 | 3.6699715 | 4.0272885 | 3.7082023 | 2.9310927 | 4.0272885 |
| mmu-miR-93-5p.ref.t5:0.t3:0.ad:0.mm:0 | 1410.00405 | 0.1081940 | 0.0882399 | 444.6899 | 0 | 0 | mmu-miR-93-5p.ref.t5:0.t3:0.ad:0.mm:0 | mmu-miR-93-5p.ref.t5:0.t3:0.ad:0.mm:0 | 0.4904528 | 0.6303569 | 1.1226739 | 1.3333864 | 1.1243616 | 1.3333864 |
| mmu-miR-21a-5p.iso.t5:0.t3:CT.ad:0.mm:0 | 64309.70315 | 0.2910704 | 0.1757690 | 444.2239 | 0 | 0 | mmu-miR-21a-5p.iso.t5:0.t3:CT.ad:0.mm:0 | mmu-miR-21a-5p.iso.t5:0.t3:CT.ad:0.mm:0 | 1.3727513 | 2.4099209 | 2.7935148 | 2.7337894 | 2.4797689 | 2.7935148 |
| mmu-miR-146b-5p.iso.t5:0.t3:G.ad:0.mm:0 | 542.44226 | 1.6358763 | 0.1742347 | 414.0365 | 0 | 0 | mmu-miR-146b-5p.iso.t5:0.t3:G.ad:0.mm:0 | mmu-miR-146b-5p.iso.t5:0.t3:G.ad:0.mm:0 | 2.6926429 | 0.5428686 | 1.1670029 | 2.3111355 | 2.5424858 | 2.6926429 |
| mmu-miR-199a-3p.iso.t5:0.t3:0.ad:A.mm:0 | 620.98234 | 1.5142002 | 0.1553404 | 397.0422 | 0 | 0 | mmu-miR-199a-3p.iso.t5:0.t3:0.ad:A.mm:0 | mmu-miR-199a-3p.iso.t5:0.t3:0.ad:A.mm:0 | 2.1517905 | 0.1785731 | 0.2175869 | 0.7617868 | 1.8248843 | 2.1517905 |
| mmu-miR-199b-3p.iso.t5:0.t3:0.ad:A.mm:0 | 620.98234 | 1.5142002 | 0.1553404 | 397.0422 | 0 | 0 | mmu-miR-199b-3p.iso.t5:0.t3:0.ad:A.mm:0 | mmu-miR-199b-3p.iso.t5:0.t3:0.ad:A.mm:0 | 2.1517905 | 0.1785731 | 0.2175869 | 0.7617868 | 1.8248843 | 2.1517905 |
| mmu-miR-21a-3p.iso.t5:c.t3:T.ad:0.mm:0 | 423.66178 | 0.0801993 | 0.2469328 | 377.9940 | 0 | 0 | mmu-miR-21a-3p.iso.t5:c.t3:T.ad:0.mm:0 | mmu-miR-21a-3p.iso.t5:c.t3:T.ad:0.mm:0 | 1.0153445 | 2.7914134 | 3.3196679 | 2.8470052 | 2.2915384 | 3.3196679 |
| mmu-miR-21a-5p.iso.t5:0.t3:C.ad:0.mm:0 | 65864.48117 | 0.2671976 | 0.2322570 | 368.7898 | 0 | 0 | mmu-miR-21a-5p.iso.t5:0.t3:C.ad:0.mm:0 | mmu-miR-21a-5p.iso.t5:0.t3:C.ad:0.mm:0 | 1.5005346 | 3.0306639 | 3.4940082 | 3.1911338 | 2.6853264 | 3.4940082 |
| mmu-miR-21a-3p.ref.t5:0.t3:c.ad:0.mm:0 | 1870.15869 | 0.1013924 | 0.2392049 | 357.4214 | 0 | 0 | mmu-miR-21a-3p.ref.t5:0.t3:c.ad:0.mm:0 | mmu-miR-21a-3p.ref.t5:0.t3:c.ad:0.mm:0 | 1.0332505 | 2.7361909 | 3.3841446 | 2.9207550 | 2.2230688 | 3.3841446 |
| mmu-miR-92a-1-5p.ref.t5:0.t3:0.ad:0.mm:0 | 135.00995 | -0.1503253 | 0.1701043 | 345.2868 | 0 | 0 | mmu-miR-92a-1-5p.ref.t5:0.t3:0.ad:0.mm:0 | mmu-miR-92a-1-5p.ref.t5:0.t3:0.ad:0.mm:0 | 0.4095784 | 1.4553068 | 1.7380425 | 1.4271687 | 0.9668157 | 1.7380425 |
| mmu-miR-181c-5p.iso.t5:0.t3:T.ad:0.mm:0 | 1523.53821 | 0.8405588 | 0.1209044 | 338.0922 | 0 | 0 | mmu-miR-181c-5p.iso.t5:0.t3:T.ad:0.mm:0 | mmu-miR-181c-5p.iso.t5:0.t3:T.ad:0.mm:0 | 1.0765788 | -0.4191428 | -0.3580316 | -0.2513222 | 0.7990521 | 1.0765788 |
| mmu-miR-181a-5p.iso.t5:0.t3:T.ad:0.mm:0 | 1668.80801 | 0.3241937 | 0.1003742 | 331.6893 | 0 | 0 | mmu-miR-181a-5p.iso.t5:0.t3:T.ad:0.mm:0 | mmu-miR-181a-5p.iso.t5:0.t3:T.ad:0.mm:0 | 0.6717940 | -0.6926857 | -0.5537966 | 0.2590926 | 0.6694544 | 0.6926857 |
| mmu-miR-21a-5p.iso.t5:0.t3:C.ad:G.mm:0 | 296.58796 | 0.2817179 | 0.2277302 | 317.3796 | 0 | 0 | mmu-miR-21a-5p.iso.t5:0.t3:C.ad:G.mm:0 | mmu-miR-21a-5p.iso.t5:0.t3:C.ad:G.mm:0 | 1.5396964 | 2.3395675 | 2.7828531 | 2.7714881 | 2.2489409 | 2.7828531 |
| mmu-miR-21a-5p.iso.t5:A.t3:CT.ad:0.mm:0 | 76.52812 | 0.9297556 | 0.3853488 | 317.1316 | 0 | 0 | mmu-miR-21a-5p.iso.t5:A.t3:CT.ad:0.mm:0 | mmu-miR-21a-5p.iso.t5:A.t3:CT.ad:0.mm:0 | 1.9237260 | 3.5530122 | 3.8607423 | 3.7776356 | 3.2155839 | 3.8607423 |
| mmu-miR-21a-5p.ref.t5:0.t3:0.ad:0.mm:0 | 74058.19837 | 0.7161811 | 0.1692574 | 311.4091 | 0 | 0 | mmu-miR-21a-5p.ref.t5:0.t3:0.ad:0.mm:0 | mmu-miR-21a-5p.ref.t5:0.t3:0.ad:0.mm:0 | 1.7579095 | 0.6885654 | 1.7312604 | 2.0926706 | 2.4943871 | 2.4943871 |
| mmu-miR-92a-3p.iso.t5:0.t3:T.ad:0.mm:0 | 25826.04849 | 0.0024922 | 0.1148568 | 307.8952 | 0 | 0 | mmu-miR-92a-3p.iso.t5:0.t3:T.ad:0.mm:0 | mmu-miR-92a-3p.iso.t5:0.t3:T.ad:0.mm:0 | 0.1266860 | 1.1327519 | 1.3676340 | 1.0886733 | 0.6160221 | 1.3676340 |
| mmu-miR-142a-5p.iso.t5:CC.t3:t.ad:0.mm:0 | 606.16226 | 1.3471400 | 0.1817580 | 303.3488 | 0 | 0 | mmu-miR-142a-5p.iso.t5:CC.t3:t.ad:0.mm:0 | mmu-miR-142a-5p.iso.t5:CC.t3:t.ad:0.mm:0 | 2.1017335 | 1.1788563 | 1.8938661 | 2.7462601 | 2.5578597 | 2.7462601 |
Working with 1071 genes
## Comparison: fa_model_cluster {.tabset}
out of 587 with nonzero total read count
adjusted p-value < 0.1
LFC > 0 (up) : 157, 27%
LFC < 0 (down) : 181, 31%
outliers [1] : 2, 0.34%
low counts [2] : 0, 0%
(mean count < 6)
[1] see ‘cooksCutoff’ argument of ?results
[2] see ‘independentFiltering’ argument of ?results
NULL
Differential expression file at: fa_model_cluster.tsv
Normalized counts matrix file at: fa_model_cluster_log2_counts.tsv
Plot top 9 genes
| baseMean | log2FoldChange | lfcSE | stat | pvalue | padj | symbol | description | Day14vsDay0 | Day1vsDay0 | Day2vsDay0 | Day3vsDay0 | Day7vsDay0 | absMaxLog2FC | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 433 | 2249.48322 | 0.9070674 | 0.3732575 | 222.37775 | 0 | 0 | 433 | 433 | 1.5714264 | 4.4169261 | 3.9961329 | 3.0406021 | 1.4994816 | 4.4169261 |
| 524 | 1825.59642 | 1.4928244 | 0.2247476 | 199.26349 | 0 | 0 | 524 | 524 | 2.5176476 | 0.7171127 | 1.3548461 | 2.3580632 | 2.4769055 | 2.5176476 |
| 581 | 830.92108 | 0.0551098 | 0.1808680 | 187.59921 | 0 | 0 | 581 | 581 | 0.3845358 | 1.6897462 | 1.5958847 | 0.9544170 | 0.6051035 | 1.6897462 |
| 10 | 248.67918 | 0.4301422 | 0.2060157 | 163.91234 | 0 | 0 | 10 | 10 | 1.2873803 | 1.4984656 | 1.6483184 | 1.7704845 | 2.0143328 | 2.0143328 |
| 143 | 61.38041 | 2.0475255 | 0.5029248 | 142.34243 | 0 | 0 | 143 | 143 | 3.0424560 | 0.7118289 | 3.1930821 | 3.9497840 | 3.9643826 | 3.9643826 |
| 343 | 64.55927 | 1.9278647 | 0.6809845 | 116.36999 | 0 | 0 | 343 | 343 | 1.9666072 | 5.1165617 | 4.7747046 | 3.7541310 | 2.1610405 | 5.1165617 |
| 209 | 91487.78417 | -0.3005822 | 0.1714544 | 107.66715 | 0 | 0 | 209 | 209 | -0.7211153 | -1.0813466 | -1.2883259 | -1.2687378 | -1.0533429 | 1.2883259 |
| 352 | 234955.42108 | 0.4043253 | 0.2683826 | 107.35545 | 0 | 0 | 352 | 352 | 1.2836260 | 1.5718652 | 2.1898987 | 2.0069401 | 2.0910592 | 2.1898987 |
| 17 | 158.85562 | 0.0399798 | 0.3281629 | 102.62231 | 0 | 0 | 17 | 17 | 0.7545601 | 1.2153195 | 2.1486236 | 2.1108204 | 1.8672980 | 2.1486236 |
| 450 | 135.84650 | 0.7362333 | 0.3167871 | 102.28819 | 0 | 0 | 450 | 450 | 1.5572398 | 0.2354885 | 1.3871195 | 2.1389756 | 2.2574049 | 2.2574049 |
| 376 | 213.56965 | 1.7275483 | 0.5997336 | 101.99441 | 0 | 0 | 376 | 376 | 2.0418641 | 4.4838385 | 4.7469158 | 4.7586558 | 2.7714175 | 4.7586558 |
| 12 | 272.48124 | -0.7432530 | 0.3095413 | 101.31684 | 0 | 0 | 12 | 12 | -1.7948377 | -1.2281486 | -1.6316536 | -2.0856325 | -2.7247396 | 2.7247396 |
| 11 | 7222.51936 | -0.3761254 | 0.2352652 | 90.01777 | 0 | 0 | 11 | 11 | -1.2622680 | -0.5538625 | -0.8623613 | -1.3182918 | -1.9443384 | 1.9443384 |
| 323 | 203.10656 | 0.0512942 | 0.3011742 | 88.51524 | 0 | 0 | 323 | 323 | 0.3118882 | 1.5420878 | 1.7928676 | 1.6646676 | 1.4653415 | 1.7928676 |
| 576 | 64.89637 | 0.2575567 | 0.5076091 | 88.65939 | 0 | 0 | 576 | 576 | 0.3177388 | 2.9555556 | 2.6581699 | 1.6229509 | 0.5102446 | 2.9555556 |
| 182 | 1348.14078 | 0.6991956 | 0.2707282 | 82.40146 | 0 | 0 | 182 | 182 | 0.6959874 | -1.0719157 | -1.0462163 | -0.2446071 | 0.2105213 | 1.0719157 |
| 387 | 133.43965 | 0.6631465 | 0.2871488 | 80.42204 | 0 | 0 | 387 | 387 | 1.6993664 | 1.6947198 | 1.3250564 | 1.9442881 | 1.9834675 | 1.9834675 |
| 142 | 5353.05737 | 0.0412670 | 0.1113550 | 79.01163 | 0 | 0 | 142 | 142 | 0.0445159 | -0.5129584 | -0.5877018 | -0.4413173 | -0.0035560 | 0.5877018 |
| 13 | 776.45634 | 1.0674236 | 0.3361205 | 78.34878 | 0 | 0 | 13 | 13 | 1.9435945 | 0.1130401 | 1.4074679 | 2.0754668 | 2.1628673 | 2.1628673 |
| 320 | 165.18074 | 1.0760742 | 0.4182942 | 78.22436 | 0 | 0 | 320 | 320 | 2.1496170 | 2.4107670 | 2.9185996 | 2.9433578 | 2.9779445 | 2.9779445 |
Working with 178 genes
Files generated contains raw count, normalized counts, log2 normalized counts and DESeq2 results.
(useful if replicating these results)
R version 3.3.0 (2016-05-03)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Debian GNU/Linux stretch/sid
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] grid parallel stats4 methods stats graphics grDevices
[8] utils datasets base
other attached packages:
[1] vsn_3.40.0 edgeR_3.14.0
[3] limma_3.28.4 DEGreport_1.5.0
[5] quantreg_5.24 SparseM_1.7
[7] org.Mm.eg.db_3.3.0 AnnotationDbi_1.34.2
[9] myRfunctions_0.1 cluster_2.0.4
[11] pheatmap_1.0.8 isomiRs_0.99.13
[13] DiscriMiner_0.1-29 dplyr_0.4.3
[15] devtools_1.11.1 gridExtra_2.2.1
[17] gtools_3.5.0 CHBUtils_0.1
[19] genefilter_1.54.2 DESeq2_1.12.2
[21] SummarizedExperiment_1.2.2 Biobase_2.32.0
[23] GenomicRanges_1.24.0 GenomeInfoDb_1.8.1
[25] IRanges_2.6.0 S4Vectors_0.10.0
[27] BiocGenerics_0.18.0 reshape_0.8.5
[29] ggplot2_2.1.0 knitr_1.13
[31] rmarkdown_0.9.6 BiocInstaller_1.22.2
loaded via a namespace (and not attached):
[1] bitops_1.0-6 RColorBrewer_1.1-2 tools_3.3.0
[4] R6_2.1.2 affyio_1.42.0 rpart_4.1-10
[7] KernSmooth_2.23-15 Hmisc_3.17-4 DBI_0.4-1
[10] lazyeval_0.1.10 colorspace_1.2-6 nnet_7.3-12
[13] withr_1.0.1 GGally_1.0.1 Nozzle.R1_1.1-1
[16] preprocessCore_1.34.0 chron_2.3-47 formatR_1.4
[19] logging_0.7-103 labeling_0.3 caTools_1.17.1
[22] scales_0.4.0 affy_1.50.0 stringr_1.0.0
[25] digest_0.6.9 foreign_0.8-66 XVector_0.12.0
[28] htmltools_0.3.5 highr_0.6 RSQLite_1.0.0
[31] BiocParallel_1.6.2 acepack_1.3-3.3 magrittr_1.5
[34] Formula_1.2-1 Matrix_1.2-6 Rcpp_0.12.5
[37] munsell_0.4.3 stringi_1.0-1 yaml_2.1.13
[40] zlibbioc_1.18.0 gplots_3.0.1 plyr_1.8.3
[43] gdata_2.17.0 lattice_0.20-33 splines_3.3.0
[46] annotate_1.50.0 locfit_1.5-9.1 geneplotter_1.50.0
[49] codetools_0.2-14 XML_3.98-1.4 evaluate_0.9
[52] latticeExtra_0.6-28 data.table_1.9.6 MatrixModels_0.4-1
[55] gtable_0.2.0 tidyr_0.4.1 assertthat_0.1
[58] xtable_1.8-2 coda_0.18-1 survival_2.39-4
[61] memoise_1.0.0